Vlo is a free, local, open source video editor with ComfyUI-backed generative AI features.
It is in early alpha and there will be bugs, but I am choosing to release it because it already makes it possible to do things which can be challenging otherwise.
Vlo requires chromium-based browsers to work. I have tested in edge and chrome, but other chromium browsers (e.g. opera) may also function. The are two fundamental reasons for this limitation.
- It uses the File System Access API for smooth and efficient file management directly on disk. This allows for a unified file management interface, whether you launch vlo on your own computer or on a remote service (e.g. runpod). You can still access your locally-stored project files. One caveat: it is best to keep your projects in a folder where you can easily find them, as clearing browser data will forget their location.
- The media renderer is built on mediabunny, which wraps webcodecs. Webcodecs has implementation differences between firefox and chrome, and during early testing, this led to noticeable lag. The Webcodecs API is the basis of frame-accurate web video, and is indispensable for a project like this.
- SAM2 points editor and masking.
- Includes automatic cropping and stitching for video inpainting workflows.
- ComfyUI bridge, allowing images, videos and timeline selections to be sent to ComfyUI
- Includes automatic aspect ratio adjustment (video models such as WAN and LTX2.3 cannot do all aspect ratios exactly).
- Built in stackable adjustments and filters
- Keyframes and spline editor for all transformations (layout, adjustments and filter effects)
If the idea of the command line makes you uncomfortable, you can skip to the one-click install section, although you still do need to the command line for SAM2 if you want segmentation (for the moment).
It is recommended to set up a Python virtual environment (venv) before installing dependencies and to run all commands within that environment. Use Python 3.10 or newer.
Linux / macOS:
git clone https://github.com/PxTicks/vlo
cd vlo
# Frontend
npm install
npm install --prefix frontend
# Backend venv (recommended)
python -m venv backend/.venv
source backend/.venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -r backend/requirements.txt #or requirements-dev.txt to include tests
cp backend/.env.example backend/.env # then edit as neededWindows (PowerShell):
git clone https://github.com/PxTicks/vlo
Set-Location vlo
# Frontend
npm install
npm install --prefix frontend
# Backend venv (recommended)
python -m venv backend/.venv
backend\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
python -m pip install -r backend/requirements.txt #or requirements-dev.txt to include tests
Copy-Item backend\.env.example backend\.envWhen backend dependencies change, update backend/pyproject.toml and regenerate the
pip requirements files with python scripts/sync-backend-requirements.py.
For SAM2 setup, make sure that torch with CUDA is installed in the backend venv, e.g.
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu128Being sure to install the version for your correct cuda environment, see https://pytorch.org/.
Then follow the official instructions at https://github.com/facebookresearch/sam2 and install it into the same active backend virtual environment.
Place any downloaded models and their associated .yaml in vlo/backend/assets/models/sams. Models can be found on Hugging Face, for example https://huggingface.co/facebook/sam2.1-hiera-large. Use the native .pt checkpoint from the official repository, such as sam2.1_hiera_large.pt. Do not use the repository's model.safetensors file with vlo's native SAM2 runtime, because that artifact uses Hugging Face Transformers parameter naming and is not compatible with facebookresearch/sam2.
Linux / macOS:
./install.shWindows:
install.batThis installs all dependencies (npm + Python via uv),
builds the frontend, and creates backend/.venv for later runs.
The one-click installer does not currently install SAM2 itself. After running it. If you want masking capabilities follow the instructions further up.
After installation, continue to Using Scripts to start Vlo.
Run ComfyUI separately on the machine that will host Vlo. By default Vlo expects
it at http://127.0.0.1:8188, but you can change that from the editor UI.
Linux / macOS:
npm run build
cd backend
python -m uvicorn main:app --host 127.0.0.1 --port 6332Windows (PowerShell):
npm run build
Set-Location backend
python -m uvicorn main:app --host 127.0.0.1 --port 6332Run both dev servers (Vite + FastAPI with hot reload):
npm run devLinux / macOS:
./run.shWindows:
run.batOpens http://127.0.0.1:6332 in your browser. Pass --no-browser to skip that.
If needed backend/.env to adjust settings (created automatically by the installer). You may be able to ignore this step.
COMFYUI_URL: defaulthttp://127.0.0.1:8188SAM2_DEVICE:auto,cpu, or a CUDA/MPS-capable value supported by your environmentSAM2_CACHE_DIR: cache location for prepared SAM2 data
For details on how workflows interact with Vlo — sidecars, widget exposure, aspect ratio processing, and the generation pipeline — see the Generation Pipeline docs. The default workflows include working sidecar examples.
Vlo is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0-or-later). See LICENSE for the full text.
Contributions are welcome, bug fixes especially (there will need to be plenty, given the stage of development). By submitting a contribution to this repository, you agree to the Individual Contributor License Agreement. To summarise the agreement in short: you retain copyright over your own code, but you give licence for it to be included as part of the vlo codebase hereafter. See CONTRIBUTING.md for the contribution process.
